Sini Decoction (SNT) is a traditional formula recognized for its efficacy in warming the spleen and stomach and dispersing cold. However, elucidating the mechanism of action of SNT remains challenging due to its complex multiple components. This study utilized a synergistic approach combining two-dimensional fluorescence difference in gel electrophoresis (2D-DIGE)-based drug affinity responsive target stability (DARTS) with label-free quantitative proteomics techniques to identify the direct and indirect protein targets of SNT in myocardial infarction. The analysis identified 590 proteins, with 30 proteins showing significant upregulation and 51 proteins showing downregulation when comparing the SNT group with the model group. Through the integration of 2D-DIGE DARTS with proteomics data and pharmacological assessments, the findings indicate that protein disulfide-isomerase A3 (PDIA3) may serve as a potential protein target through which SNT provides protective effects on myocardial cells during myocardial infarction.
Myocardial Infarction/genetics* ; Proteomics/methods* ; Drugs, Chinese Herbal/chemistry* ; Animals ; Protein Disulfide-Isomerases/genetics* ; Male ; Two-Dimensional Difference Gel Electrophoresis/methods* ; Humans ; Rats ; Rats, Sprague-Dawley ; Electrophoresis, Gel, Two-Dimensional

Biomanufacturing has emerged as a crucial driving force for efficient material conversion through engineered cells or cell-free systems. However, the intrinsic spatiotemporal heterogeneity, complexity, and dynamic characteristics of these processes pose significant challenges to systematic understanding, optimization, and regulation. This review summarizes essential methodologies for multi-omics data acquisition and analyses for bioprocesses and outlines modelling approaches based on multi-omics data. Furthermore, we explore practical applications of multi-omics and modelling in fine-tuning process parameters, improving fermentation control, elucidating stress response mechanisms, optimizing nutrient supplementation, and enabling real-time monitoring and adaptive adjustment. The substantial potential offered by integrating multi-omics with computational modelling for precision bioprocessing is also discussed. Finally, we identify current challenges in bioprocess optimization and propose the possible solutions, the implementation of which will significantly deepen understanding and enhance control of complex bioprocesses, ultimately driving the rapid advancement of biomanufacturing.
Fermentation ; Genomics/methods* ; Biotechnology/methods* ; Proteomics/methods* ; Models, Biological ; Metabolomics/methods* ; Bioreactors ; Multiomics

Adolescents and young adults (AYAs) are one of the major populations susceptible to tuberculosis. However, little is known about the unique characteristics and diagnostic biomarkers of tuberculosis in this population. In this study, 81 AYAs were recruited, and the high-quality serum proteome of the AYAs with tuberculosis was profiled by quantitative proteomics. The data of serum proteomics indicated that the relative abundance of hemoglobin and apolipoprotein was significantly reduced in the patients with active tuberculosis (ATB). The pathway enrichment analysis showed that the downregulated proteins in the ATB group were mainly involved in the antioxidant and cell detoxification pathways, indicating extensive oxidative stress damage. Random forest (RF) and extreme gradient boosting (XGBoost) were employed to evaluate protein importance, which yielded a set of candidate proteins that can distinguish between ATB and non-ATB. The analysis with the support vector machine algorithm (recursive feature elimination) suggested that the combination of apolipoprotein A-I (APOA1), hemoglobin subunit beta (HBB), and hemoglobin subunit alpha-1 (HBA1) had the highest accuracy and sensitivity in diagnosing ATB. Meanwhile, the levels of hemoglobin (HGB) and albumin (ALB) can be used as blood biochemical indicators to evaluate changes in the protein levels of APOA1 and HBB. This study established the serum proteome landscape of AYAs with tuberculosis and identified new biomarkers for the diagnosis of tuberculosis in this population.
Humans ; Proteomics/methods* ; Biomarkers/blood* ; Adolescent ; Young Adult ; Apolipoprotein A-I/blood* ; Machine Learning ; Tuberculosis/blood* ; Proteome/analysis* ; Male ; Hemoglobins/analysis* ; Female ; Blood Proteins/analysis* ; Adult

Phages, as obligate bacterial and archaeal parasites, constitute a virus group of paramount ecological significance due to their exceptional abundance and genetic diversity. These biological entities serve as critical regulators in Earth's ecosystems, driving biogeochemical cycles, energy fluxes, and ecosystem services across terrestrial and marine environments. Within soil microbiomes, phages function as microbial "dark matter," maintaining the soil-plant system balance through precise modulation of the microbial community structure and functional dynamics. Despite the growing research interests in soil phages in recent years, the proportion of such studies in environmental virology remains disproportionately low, which is primarily attributed to researchers' limited familiarity with the research methodologies for phage microecology, incomplete technical frameworks, and inherent challenges posed by soil environmental complexity. To address these challenges, this review synthesizes cutting-edge methodologies for soil phage investigation from four aspects: (1) tangential flow filtration (TFF)-based phage enrichment strategies; (2) integrated quantification approaches combining double-layer agar plating, epifluorescence microscopy, and flow cytometry; (3) multi-omics analytical pipelines leveraging metagenomics and viromics datasets; and (4) computational frameworks merging machine learning algorithms with eco-evolutionary theory for deciphering phage-host interaction networks. Through comparative analysis of methodological principles, technical merits, and application scopes, we establish a comprehensive workflow for soil phage research. Future research in this field should prioritize: (1) construction of soil phage resource libraries, (2) exploration of RNA phages based on transcriptomes, (3) functional characterization of unknown genes, and (4) deep integration and interaction validation of multi-omics data. This systematic methodological synthesis provides critical technical references for addressing fundamental challenges in characterizing soil phages regarding the community structure, functional potential, and interaction mechanisms with hosts.
Bacteriophages/physiology* ; Soil Microbiology ; Ecosystem ; Microbiota ; Metagenomics/methods*

Small urban wetlands are widely distributed and susceptible to human activities, serving as important sources and sinks of carbon. Microorganisms play a crucial role in carbon cycle, while limited studies have been conducted on the microbial diversity in small urban wetlands and the functions of microbiome in carbon fixation and metabolism. To probe into the microbiome-driven carbon cycling in small urban wetlands and dissect the composition and functional groups of microbiome, we analyzed the relationships between the microbiome structure, element metabolism pathways, and habitat physicochemical properties in sediment samples across three small wetlands in Huzhou City, and compared them with natural wetlands in the Zoige wetland. High-throughput sequencing of 16S rRNA gene amplicons and metagenomics was employed to determine the species and functional groups. Sixty medium to high-quality metagenome-assembled genomes (MAGs) were constructed, including 55 bacterial and 5 archaeal taxa, and their potential in driving elemental cycles were analyzed, with a focus on carbon fixation. Several bacterial species were found to encode a nearly complete carbon fixation pathway, including the Calvin cycle, the reductive tricarboxylic acid cycle, the Wood-Ljungdahl pathway, and the reductive glycine pathway. There were several potential novel carbon-fixing bacterial members, such as those belonging to Syntrophorhabdus (Desulfobacterota) and UBA4417 (Bacteroidetes), which had high relative abundance in the wetland microbiome. Unveiling the genetic potential of these functional groups to facilitate element cycling is of great scientific importance for enhancing the carbon sequestration capacity of small urban wetlands.
Wetlands ; Microbiota/genetics* ; Carbon Cycle/genetics* ; Bacteria/classification* ; RNA, Ribosomal, 16S/genetics* ; China ; Cities ; Geologic Sediments/microbiology* ; Archaea/classification* ; Metagenomics ; Metagenome

Bacillus velezensis DJ1 exhibits broad-spectrum antagonistic activity against diverse phytopathogenic fungi, while its biocontrol mechanisms against Fusarium graminearum, the causal agent of maize stalk rot, remain poorly characterized. In this study, we integrated genomics and transcriptomics to elucidate the antifungal mechanisms of strain DJ1. The results demonstrated that DJ1 inhibited F. graminearum with the efficacy of 64.4%, while its polyketide crude extract achieved the control efficacy of 55% in pot experiments against this disease. Whole-genome sequencing revealed a single circular chromosome (3 929 792 bp, GC content of 47%) harboring 12 biosynthetic gene clusters for secondary metabolites, six of which encoded known antimicrobial compounds (macrolactin H, bacillaene, difficidin, surfactin, fengycin, and bacilysin). Transcriptomic analysis identified 243 differentially expressed genes (152 upregulated and 91 downregulated, P < 0.05), which were potentially associated with the antagonistic activity against F. graminearum. KEGG enrichment analysis highlighted activation (P < 0.05) of cysteine/methionine metabolism, pentose phosphate pathway, and polyketide biosynthesis pathways, indicating that DJ1 employed synergistic strategies involving antimicrobial compound synthesis, energy metabolism enhancement, and nutrient competition to suppress pathogens. This study provides a theoretical foundation for developing novel microbial resources and application technologies to combat phytopathogenic fungi.
Fusarium/drug effects* ; Bacillus/metabolism* ; Plant Diseases/prevention & control* ; Antifungal Agents/pharmacology* ; Genomics ; Zea mays/microbiology* ; Transcriptome ; Gene Expression Profiling ; Antibiosis ; Multigene Family ; Multiomics

Japanese spotted fever(JSF)is an infectious disease caused by Rickettsia japonica,with nonspecific clinical symptoms and a high risk of misdiagnosis.We reported a case of JSF,in which Rickettsia japonica was detected in blood cells by metagenomic next-generation sequencing.The patient recovered after treatment with doxycycline.This report provides a reference for the clinical diagnosis and treatment of JSF.
Humans ; High-Throughput Nucleotide Sequencing ; Metagenomics ; Rickettsia/isolation & purification* ; Spotted Fever Group Rickettsiosis/microbiology*

Recent advancements in molecular techniques such as real-time PCR, isothermal amplification, next-generation sequencing, metagenomics, microarray, and CRISPR-infectious disease diagnostics have significantly evolved and improved over the past years. This overview will explore the innovations that have shaped the molecular diagnostics workflow, as well as the progress made in these innovative techniques. Additionally, it will address existing gaps, unmet needs, and the potential future directions for further enhancing diagnostic capabilities in the field.

BACKGROUND: Hepatic inflammatory cell accumulation and the subsequent systematic inflammation drive acute-on-chronic liver failure (ACLF) development. Previous studies showed that the vagus nerve exerts anti-inflammatory activity in many inflammatory diseases. Here, we aimed to identify the key molecule mediating the inflammatory process in ACLF and reveal the neuroimmune communication arising from the vagus nerve and immunological disorders of ACLF. METHODS: Proteomic analysis was performed and validated in ACLF model mice or patients, and intervention animal experiments were conducted using neutralizing antibodies. PNU-282987 (acetylcholine receptor agonist) and vagotomy were applied for perturbing vagus nerve activity. Single-cell RNA sequencing (scRNA-seq), flow cytometry, immunohistochemical and immunofluorescence staining, and clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) technology were used for in vivo or in vitro mechanistic studies. RESULTS: The unbiased proteomics identified C-X-C motif chemokine ligand 9 (CXCL9) as the greatest differential protein in the livers of mice with ACLF and its relation to the systematic inflammation and mortality were confirmed in patients with ACLF. Interventions on CXCL9 and its receptor C-X-C chemokine receptor 3 (CXCR3) improved liver injury and decreased mortality of ACLF mice, which were related to the suppressing of hepatic immune cells' accumulation and activation. Vagus nerve stimulation attenuated while vagotomy aggravated the expression of CXCL9 and the severity of ACLF. Blocking CXCL9 and CXCR3 ameliorated liver inflammation and increased ACLF-associated mortality in ACLF mice with vagotomy. scRNA-seq revealed that hepatic macrophages served as the major source of CXCL9 in ACLF and were validated by immunofluorescence staining and flow cytometry analysis. Notably, the expression of CXCL9 in macrophages was modulated by vagus nerve-mediated cholinergic signaling. CONCLUSIONS Our novel findings highlighted that the neuroimmune communication of the vagus nerve-macrophage-CXCL9 axis contributed to ACLF development. These results provided evidence for neuromodulation as a promising approach for preventing and treating ACLF.
Animals ; Mice ; Chemokine CXCL9/metabolism* ; Vagus Nerve/physiology* ; Acute-On-Chronic Liver Failure/metabolism* ; Humans ; Male ; Mice, Inbred C57BL ; Proteomics ; Flow Cytometry ; Receptors, CXCR3/metabolism*

Research on IgG4-related disease (IgG4-RD), an autoimmune condition recognized to be a unique disease entity only two decades ago, has processed from describing patients' symptoms and signs to summarizing its critical pathological features, and further to investigating key pathogenic mechanisms. Challenges in gaining a better understanding of the disease, however, stem from its relative rarity-potentially attributed to underrecognition-and the absence of ideal experimental animal models. Recently, with the development of various high-throughput techniques, "omics" studies at different levels (particularly the single-cell omics) have shown promise in providing detailed molecular features of IgG4-RD. While, the application of omics approaches in IgG4-RD is still at an early stage. In this paper, we review the current progress of omics research in IgG4-RD and discuss the value of machine learning methods in analyzing the data with high dimensionality.
Humans ; Immunoglobulin G4-Related Disease/metabolism* ; Immunoglobulin G/metabolism* ; Machine Learning ; Animals ; Proteomics/methods*